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ENVIRONMENTAL AND ECOLOGICAL CHEMISTRY – Vol. III – Multimedia Fate and Transport of Organic Pollutants - Michael Matthies

©Encyclopedia of Life Support Systems (EOLSS)

MULTIMEDIA FATE AND TRANSPORT OF ORGANIC POLLUTANTS Michael Matthies Institute of Environmental Systems Research, University of Osnabrück, Osnabrück, Germany Keywords: environmental fate, exposure, exposure assessment, multimedia modeling, environmental and health risk, persistence, long range environmental transport potential, mass balance equation, characteristic travel distance, environmental transport Contents 1. Introduction 2. Mass Balance Models 2.1. Level I: Equilibrium, No Inflow or Outflow, No Degradation 2.2. Level II: Equilibrium, With Inflow, Outflow and Degradation, Steady State 2.3. Level IIdyn: Equilibrium, With Inflow, Outflow and Degradation, Nonsteady State 2.4. Level III: No Thermodynamic Equilibrium, Steady State 2.5. Level IV: No Thermodynamic Equilibrium, Nonsteady State 3. Persistence and Long-Range Transport Potential 3.1. Persistence 3.2. Long-Range Transport Potential 4. Assessment of Models 5. Strengths and Limitations of Multimedia Models 6. Conclusions Glossary Bibliography Biographical Sketch Summary Environmental transport and fate of organic chemical pollutants are described by a system of mass balance equations which take into account the various physical, chemical and biological exchange and transformation processes in and among the environmental compartments. In multimedia models, the total environment is represented as a set of spatially homogeneous boxes; one box for each environmental compartment in which the chemical is assumed to be evenly distributed. The number, size, properties etc. of boxes, e.g. air, water and soil, can vary. Four levels of increasing complexity are defined, depending on the assumptions of thermodynamic equilibrium, steady and nonsteady state or intermedia mass transfer. Mass transfer is modeled by advective transport, e.g. deposition, and diffusive exchange, e.g. volatilization. Multimedia models give insight into the dynamics of environmental transport and transformation of organic substances independent of the emission compartment. They are used to determine the overall persistence and long-range transport of organic pollutants and to estimate the concentrations/doses to which human population or

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ecosystems are or may be exposed. Multimedia models are an essential part of risk assessment of new and existing chemicals. 1. Introduction Organic chemical substances with different physical and chemical properties are emitted into the environment due to the production, manufacturing, use and disposal of man-made chemical products. In order to understand and quantify the fate and distribution of organic pollutants in the environment, the main dynamic processes of substance transport and transformation in and between environmental media need to be described quantitatively. The environment is a spatially multi-structured, temporally changing system made up of abiotic and biotic components, which interact via physical processes, such as air flow and water flow, and chemical processes, such as nutrient consumption and excretion. A common, pragmatic procedure is to divide the system into the environmental compartments air, water and soil, which are composed of various amounts of gaseous, liquid, amorphous and solid phases, and which exchange substances and energy. This division is based on the assumption that environmental systems can be perceived as mixed phases. The transport and conversion processes such as advection, diffusion and degradation, which lead to a temporal change and spatial distribution of substances, take place both within and between phases. Environmental media are frequently understood as compartments, in other words, as spatial sections, volumes or boxes, which are homogenous within themselves. Chemical substances are intermixed within them with negligible temporal delay. The assumption upon which this approach is based, which stipulates that the intramedia intermixing occurs much more quickly than intermedia exchange, however, has to be examined in each individual case. The environment (or a section of it) is described as a multi-compartment system (or multimedia system). The spatial complexity is reduced to an interlinked system of environmental compartments with distinct geometric, physical, chemical and biological properties, which interact with the chemical substances and exchange them over the compartment boundaries. Multimedia fate models are used for understanding and quantifying the distribution and transport of organic substances between air, water, soil, and other compartments. They describe the relations between emissions and exposure concentrations by solving the mass balance equations for these compartments. In order to do so quantitative expressions for the mass transfer and degradation process rates need to be formulated. This chapter adopts the approach of Donald Mackay to multimedia mass balance models including definition of increasing levels of complexity. 2. Mass Balance Models The basis for modeling the distribution of substances in the environment is the principle of mass conservation, which states that the rate of change of mass in a system equals the difference of inputs and outputs. It is assumed that adverse ecotoxic effects that may occur only negligibly affect the environmental distribution, in other words, feedback between the effects, and distribution can be neglected. Following the proposal of the pioneering work of Donald Mackay, four levels I to IV of increasing complexity are defined. These levels differ in their consideration of exchange and degradation

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processes, as well as dynamics (see Table 1.). The most significant aspect is the differentiation between steady state and (thermodynamic) equilibrium. Steady state means that everything in the system remains constant. The substance masses of all

environmental compartments do not change with time, i.e. 0id mdt

= where i is the

number of mixed compartments. (Thermodynamic) equilibrium is a special case when the concentration ratios between all media (compartments) are at their equilibrium partition ratio.

Level Thermodynamic

equilibrium

In- and

Outflow

Degradation Intermedia

mass

transfer

Steady

state

Output

I Yes No No No Not

applicable

Equilibrium

mass

distribution

II Yes Yes Yes No Yes Steady state

input/output

balance

IIdyn Yes Yes Yes No No As II, but

dynamic mass

and

concentration

course

III No Yes Yes Yes Yes Steady state

input/output

balance with

intermedia

exchange

IV No Yes Yes Yes No As III, but

dynamic mass

and

concentration

course

Table 1: Mass balance models of increasing complexity

In Level I, an isolated system that exchanges neither mass nor chemical potential with its environment is described. The substance mass within the system is merely distributed to the compartments. This equilibrium state occurs immediately and without delay, since it is assumed that the system is in thermodynamic equilibrium at all times.

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In Level II, the assumption of thermodynamic equilibrium is retained, but continual inflows and outflows, as well as losses through degradation, are additionally taken into account. The original Level II, which assumes steady state, was later extended to the dynamic, nonsteady-state case of Level IIdyn, which simulates the fate of concentrations over the whole time scale. In Levels III and IV, additional internal advective and diffuse exchange processes, such as deposition, volatilization and sedimentation, are taken into account. These processes lead to a temporal delay and to a deviation of any state from the thermodynamic equilibrium, due to resistances at the phase boundaries. Level III models look only at steady state, while Level IV models deal with the general nonsteady-state solution over the whole time-scale. In order to be able to compare the four levels with one another, Donald Mackay introduced the “Unit World” concept. The environment is divided into the main compartments air, soil, surface water, and sediment. Volumes, boundary areas and other environmental properties are parameterized for either a global or regional environment. EUSES (European System for the Evaluation of Substances) assumes area of 200 by 200 kilometers, which is divided into 97 percent soil and 3 percent fresh water. The height of atmospheric mixing layer is 1000 meters; depth of the water is 3 meters, that of soil is 10 centimeters, and that of sediment 3 centimeters. These lead to the volumes given in Figure 1. For simplification purposes, the three soils, considered in EUSES, were combined into one.

Figure 1: Regional multimedia distribution model with four compartments; modified

from EUSES – the European Union System for the Evaluation of Substances, European Chemicals Bureau, Ispra (1996)

Mass balance models can equivalently be formulated by using fugacity and fugacity capacities. Fugacity corresponds to the partial pressure in a compartment and can be viewed as the “escaping tendency” of a substance. The following basic equation applies C f Z= × (1) where C is the concentration of a substance (here: mol m-3), f is the fugacity (Pa) and Z is the fugacity capacity (mol m-3 Pa-1)). In thermodynamic equilibrium the fugacities

if and jf of two adjacent phases i and j are equal. This leads to:

( ) ( ) i j i i j j i j ijC C f Z f Z Z Z K= × × = = (2)

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The partition coefficient

ijK can therefore be expressed by equilibrium concentration ratio or the quotient of the fugacity capacities. Different fugacities in adjacent phases show that the system is not in equilibrium. The fugacity concept enables the differences of the varying model types Level I to IV to be shown clearly (see Figures 2, 4 and 5). 2.1. Level I: Equilibrium, No Inflow or Outflow, No Degradation With this level it is assumed that the whole substance amount in the system is infinitely rapid distributed to all compartments in accordance with the partition coefficients. The substance mass in the system remains constant, since there are neither inflows, outflows nor degradation. The result is the equilibrium distribution of a substance in an evaluative environment, as it would tend to adapt itself if exchange were uninhibited. The compartment of entry is unimportant, because redistribution is assumed to be instantaneous. If the whole substance mass in the system

tm (kg) consisting of n compartments with the volumes

1,.., nV V (m3) is known, the masses 1,..., nm m and concentrations

1,..., nC C need to be determined. The following serves as a mass balance equation

t 1 1 2 2 n nm C V C V C V= × + × +…+ × . (3) In (thermodynamic) equilibrium the following applies: 1 1/ i iC C K= , where i is from 1 to n and 11K is 1. This leads to:

t 1 1 1 21 2 1 1n nm C V C K V C K V= × + × × + + × ×… (4)

( )1 t 1 21 2 1 .n nC m V K V K V= + × + + ×… (5) From this the partition coefficients

ijK can be used to calculate all other concentrations Ci, and the masses can also be determined with the use of

i i im V C= × . (6) The principle is portrayed in Figure 2. Compartments 1, 2,...,n are assumed to be communicating pipes or boxes. Uninhibited exchange is possible between the boxes. All boxes are filled to the same height ( h ). The system is in equilibrium. Analogously, a system of communicating pipes filled with water can be imagined. The substance masses mi are represented by the volumes in the pipes. The height h is the fugacity f and, as the measure of the equilibrium state, is the same height in all pipes. The fugacity capacity iZ is represented by width b . According to Eq. (1), the areas from height h (= fugacity f ) multiplied by width b (= fugacity capacity iZ ) lead to concentrations

iC . The depths

il correspond to the compartment volumes iV .

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The only substance properties, which are required for calculation by Level I model, are the partition coefficients

ijK between adjacent compartments. Partition coefficient between air and water, KAW , can be computed from Henry's law constant H by dividing it by a factor R T× , where R is the gas constant and T is the absolute temperature. For organic substances, H is given by the ratio of vapor pressure °p and water solubility

WS of the pure compound. Partition coefficient between soil and water,

SWK , can be estimated from n-octanol/water partition coefficient OWK , which is based

on the assumption that sorption to soil particles is governed by lipophilic soil organic carbon content OC. Many regressions revealed a close relation between

OWK and OCK ,

which is the partition coefficient between OC and water. Finally, SWK is estimated by

multiplying OCK with the fraction of OC and the ratio of the bulk soil density and soil

water content. Similar approach is applied to the estimation of the partition coefficient between sediment and water. Partition coefficient between air and soil is immediately given as the ratio of

AWK and SWK (see Ecological Chemistry).

For the three substances 2,3,7,8-tetrachlorodibenzo-p-dioxin (TCDD), linear alkylbenzene sulfonate (LAS) and benzene, the mass distribution to the media of air, water, soil and sediment are calculated for the simplified regional scenario from Figure 1. Substance data are given in Figure 3 together with the results of the Level I model. The predominant percentage of 2,3,7,8-TCDD accumulates in the soil and sediment, while LAS mainly resides in water, and benzene accumulates in the air. This leads to the conclusion that benzene is mainly dispersed by wind, LAS is carried with water flow, while 2,3,7,8-TCDD is rather immobile.

Figure 2: Multimedia mass balance model Level I

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Figure 3: Mass percentages for three sample compounds calculated with Level I and the model presented in Figure 1; 2,3,7,8-TCDD (2,3,7,8-tetrachloro-dibenzo-p-dioxin),

LAS (linear alkyl benzene sulfonate)

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Bibliography Boethling R.S. and Mackay D. (2000). Handbook of Property Estimation Methods for Chemicals. Environmnetal and Health Sciences. Lewis Publ.: Boca Raton. [Compilation of estimation methods of substance properties needed for environmental modeling.]

Brandes L.J., den Hollander H., van de Meent D. (1996). Simple Box 2.0: a nested multimedia fate model for evaluating the environmental fate of chemicals. National Institute of Public Health and the Environment: Bilthoven (Niederlande). Report no. 719101029. [This report describes in detail a spatially nested approach of multimedia models.]

Cowan C., Mackay D., Feijtel T., van de Meent D., di Guardo A., Davies J. and Mackay N. (1995). The Multi-Media Fate Model: A vital tool for predicting the fate of chemicals. SETAC Press: Pensacola. [Comparison of various multimedia models and their application for regulatory purposes.]

European Commission (1996). Technical Guidance Document in Support of the Commission Directive 93/67/EEC on Risk Assessment for New Notified Substances and the Commission Regulation (EC) 1488/94 on Risk Assessment for Existing Substances, Parts I-IV. Office for Official Publications of the European Communities: Luxembourg. [Describes methods and models for exposure and risk assessment; includes a regional multimedia distribution model.]

Mackay D. and Paterson S. (1979). Finding fugacity feasible. Environ. Sci. Technol. 13, 1218-1223. [The first scientific paper on multimedia modeling.]

Mackay D. (2001). Multimedia Environmental Models. The Fugacity Approach. 2nd ed. Lewis Publ.: Boca Raton. [A basic textbook for multimedia fate modeling. Recommended for further reading.]

Mackay D., Shiu W. Y. S., Ma K. C. (1992). Illustrated Handbook of Physical-Chemical Properties and Environmental Fate for Organic Chemicals. Lewis Publ.: Boca Raton. [Collection of substance data for several persistent substance classes; contains measured and estimated literature data with references.]

Scheringer M. (2002): Persistence and Spatial Range of Environmental Chemicals. Wiley-VCH: Weinheim. [This book describes coupled multimedia models to calculate global transport and persistence. It is recommended as an introduction to hazard and risk assessment of persistent organic pollutants (POPs).]

Trapp S., Matthies M. (1998). Chemodynamics and Environmental Modeling. An Introduction. Springer: Berlin. [Textbook for graduate students and self study.] Biographical Sketch Professor Michael Matthies studied physics at the Universities in Münster and München, Germany. In 1971 he finished his undergraduate studies with B.Sc. thesis in Medical Physics. In 1975 he received his

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Ph.D. in Physical Chemistry from the University of München, Faculty of Chemistry. His Ph.D. thesis was on hydrogen bonds in energy rich biochemical compounds. From 1976–1977 he worked as a research associate in at Institute of Biophyics, University of Giessen. Two years later he became a research associate at the National Centre of Environment and Health in München-Neuherberg. He worked on radiation risk analysis, radioecology and chemical exposure and risk assessment. In 1987 he became the head of the Project Group on Hazard Assessment of Chemicals. In 1992 he was appointed as a full professor of Applied Systems at the University of Osnabrück. He founded the Institute for Environmental Systems Research in 1994 and is its director since then. His major interests are environmental systems science, systems ecology and biogeochemical cycles, transport modeling of pollutants in air, soil and water, exposure and risk assessment, integrated modeling and assessment. Professor Matthies participated in several national and international projects on exposure modeling, comparative risk assessment, long-range transport modeling of persistent organic pollutants and geo-referenced exposure assessment. The results of his research are documented in over 150 articles in scientific journals, proceedings and handbooks and 40 scientific reports and books. He served as a consultant for international organizations (OECD, EU) and various national agencies such as the German Federal Environmental Protection Agency and Federal Ministry of Research and Technology.

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